If the IoU of a pair of boxes exceeds the maximum threshold, then either one of the predicted boxes is incorrect or one of the predicted variances is incorrect.
Assuming the bounding box is wrong, we can remove the box with the lower likelihood.
Otherwise, we can assume the variance is inaccurate and increase the variance of the less likely box such that \(t\)  would equal the observed IoU.
The former is referred to as Hard NMS while the latter is analogous to Soft NMS [1]}. The effect of this choice is examined in the ablation study in Section REF .
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